Abstract:

We implement a high-order finite-element application, which performs the numerical simulation of seismic wave propagation resulting for instance from earthquakes at the scale of a continent or from active seismic acquisition experiments in the oil industry, on a large cluster of NVIDIA Tesla graphics cards using the CUDA programming environment and non-blocking message passing based on MPI. Contrary to many finite-element implementations, ours is implemented successfully in single precision, maximizing the performance of current generation GPUs. We discuss the implementation and optimization of the code and compare it to an existing very optimized implementation in C language and MPI on a classical cluster of CPU nodes. We use mesh coloring to efficiently handle summation operations over degrees of freedom on an unstructured mesh, and non-blocking MPI messages in order to overlap the communications across the network and the data transfer to and from the device via PCIe with calculations on the GPU. We perform a number of numerical tests to validate the single-precision CUDA and MPI implementation and assess its accuracy. We then analyze performance measurements and depending on how the problem is mapped to the reference CPU cluster, we obtain a speedup of 20x or 12x.

(Dimitri Komatisch, Gordon Erlebacher, Dominik Göddeke and David Michéa: “High-order finite-element seismic wave propagation modeling with MPI on a large GPU cluster”, accepted for publication in: Journal of Computational Physics, Jun. 2010. PDF preprint. DOI link.)

The objective of this one-day workshop is to investigate opportunities in accelerating data management systems and workloads (which include traditional OLTP, data warehousing/OLAP, ETL, Streaming/Realtime, and XML/RDF Processing) using various processor architectures  (e.g., commodity and specialized Multi-core CPUs, Many-core GPUs, and FPGAs), storage systems (e.g., Storage-class Memories like SSDs and Phase-change Memory), and multicore programming strategies like OpenCL.

More information and the full call can be found here: http://www.adms-conf.org/

Read the rest of this entry »

HOOMD-blue stands for Highly Optimized Object-oriented Many-particle Dynamics — Blue Edition. It performs general-purpose particle dynamics simulations on a single workstation, taking advantage of  NVIDIA GPUs to attain a level of performance equivalent to dozens of processor cores on a fast cluster.

HOOMD-blue 0.9.0 is a major new release. Highlights include:

• Support for Fermi generation GPUs
• Performance enhancements
• New pair potentials
• Particle data is now accessible from hoomd scripts
• Binary format dump files for simulation restarts
• Numerous small enhancements to enable easily restartable jobs
• 2D simulations are now possible
• Integration methods can now be applied to specified groups of particles
• All IMD commands issued by VMD are now understood
• … and more

HOOMD-blue 0.9.0 is available for download under an open source license.

RenderStream has recently announced a 16-GPU version of their VDAC (Visual and Data Analysis Cluster) product. It includes up to 16 GPUs (dual-GPU boards) in a single rack-mountable chassis, along with independent power supply, host CPUs and memory. The individual cards have an exclusive x16 full-bandwidth PCIe connection. The full article is available here: http://blog.renderstream.com/?p=600

The goal of the session, held in conjunction with Euro-Par 2010 on August 30th, 2010 in Ischia – Naples, Italy, is to present latest research in how hardware and software (yet) unconventional for HPC is/can be used to reach given goals such as best performance/watt, with according programming models, compiler techniques and tools. Thus, suggested topics for papers include, but are not limited to the following:

• Innovative use of hardware and software unconventional for HPC
• HPC applications or visualizations in connection with HPC on GPUs (GPGPU), IBM Cell, Low Power Processors, FPGAs, Visualization cards etc.
• Cluster/Grid solutions using unconventional hardware, e.g. clusters of PS3s, GPUs, Low Power Processors, FPGAs etc.
• Performance and scalability studies in HPC using unconventional hardware
• Reconfigurable Computing for HPC
• Performance modeling, analysis and tools for HPC with unconventional hardware
• New or adapted/extended (parallel) programming models for HPC with unconventional hardware

The submission deadline is June 14th, and the full call for papers along with further information and submission instructions can be found at http://uchpc10.cs.tum.edu.

RIKEN, one of the most prestigious research institutes in Japan, is the site of an upcoming computing workshop to be keynoted by NVIDIA CEO Jen–Hsun Huang. RIKEN conducts research across a wide range of fields, including physics, chemistry, medical science, biology, and engineering. The workshop will be held 1/28/10 – 1/29/10. See https://reg-nvidia.jp/public/seminar/view/3 for full details.  In addition to keynote speeches by Jen-Hsun Huang and Professor Takayuki Aoki from Tokyo Institute of Technology, guest speakers at the event include Prof. Lorena Barba from Boston University, Mr. Mr. Eiji Fujii from Square ENIX, Dr. Mark Harris from NVIDIA (and GPGPU.org), and Dr. James Phillips from The University of Illinois at Urbana-Champaign.

From the workshop webpage:

“Accelerated Computing” is an old concept that is recently redefined in High-Performance Computing. It was started by dedicated machines like GRAPEs, but a great revolution has been occurring fueled by recent advancement in GPU Computing, both in hardware and in software such as CUDA C and OpenCL. This conference aims to review cutting edge technologies and scientific applications, as well as to discuss the future of the “Accelerator” approach in scientific and industrial HPC. Please join the conference for fruitful discussions on the future of HPC with highly-parallel processors.

The presentation slides from the Supercomputing 2009 full-day tutorial “High-Performance Computing with CUDA” are now available at http://gpgpu.org/sc2009.

Abstract:

NVIDIA’s CUDA is a general-purpose architecture for writing highly parallel applications. CUDA provides several key abstractions—a hierarchy of thread blocks, shared memory, and barrier synchronization—for scalable high-performance parallel computing. Scientists throughout industry and academia use CUDA to achieve dramatic speedups on production and research codes. The CUDA architecture supports many languages, programming environments, and libraries including C, Fortran, OpenCL, DirectX Compute, Python, Matlab, FFT, LAPACK, etc.

In this tutorial NVIDIA engineers will partner with academic and industrial researchers to present CUDA and discuss its advanced use for science and engineering domains. The morning session will introduce CUDA programming, motivate its use with many brief examples from different HPC domains, and discuss tools and programming environments. The afternoon will discuss advanced issues such as optimization and sophisticated algorithms/data structures, closing with real-world case studies from domain scientists using CUDA for computational biophysics, fluid dynamics, seismic imaging, and theoretical physics.

24th International Conference on Supercomputing (ICS’10)
June 1-4, 2010
Epochal Tsukuba (Tsukuba International Congress Center)
Tsukuba, Japan
Sponsored by ACM/SIGARCH

ICS is the premier international forum for the presentation of research results in high-performance computing systems.  In 2010 the conference will be held at the Epochal Tsukuba (Tsukuba International Congress Center) in Tsukuba City, the largest high-tech and academic
city in Japan.

Papers are solicited on all aspects of research, development, and application of high-performance experimental and commercial systems. Special emphasis will be given to work that leads to better understanding of the implications of the new era of million-scale parallelism and Exa-scale performance; including (but not limited to): Read the rest of this entry »

Abstract:

High-performance scientific computing has recently seen a surge of interest in heterogeneous systems, with an emphasis on modern Graphics Processing Units (GPUs). These devices offer tremendous potential for performance and efficiency in important large-scale applications of computational science. However, exploiting this potential can be challenging, as one must adapt to the specialized and rapidly evolving computing environment currently exhibited by GPUs. One way of addressing this challenge is to embrace better techniques and develop tools tailored to their needs. This article presents one simple technique, GPU run-time code generation (RTCG), and PyCUDA, an open-source toolkit that supports this technique.
In introducing PyCUDA, this article proposes the combination of a dynamic, high-level scripting language with the massive performance of a GPU as a compelling two-tiered computing platform, potentially offering significant performance and productivity advantages over conventional single-tier, static systems. It is further observed that, compared to competing techniques, the effort required to create codes using run-time code generation with PyCUDA grows more gently in response to growing needs. The concept of RTCG is simple and easily implemented using existing, robust tools. Nonetheless it is powerful enough to support (and encourage) the creation of custom application-specific tools by its users. The premise of the paper is illustrated by a wide range of examples where the technique has been applied with considerable success.

Preprint at arXiv

(Andreas Klöckner, Nicolas Pinto, Yunsup Lee, Bryan Catanzaro, Paul Ivanov, Ahmed Fasih. PyCUDA: GPU Run-Time Code Generation for High-Performance Computing, submitted. http://arxiv.org/abs/0911.3456)

Registration is now open for the Workshop on Non-Traditional Programming Models for High-Performance Computing (part of The Los Alamos Computer Science Symposium). The symposium and workshop will be held in Santa Fe, New Mexico on October 13-14, 2009.

The goals of the workshop are two-fold:

1. To begin to identify, specify and capture in writing, the problematic issues and barriers inherent in today’s scientific software construction process.
2. To expose attendees to non-traditional programming models with the express purpose of igniting thought and discussion on the future of large-scale scientific programming.

The one-day workshop will consist of three sequential tracks, each lead by a moderator/facilitator. The tracks will include a small number of speakers who will each present a short position paper outlining their thoughts on current problems and how specific non-traditional techniques may be applied to address these issues. Following the presentations, the moderator will lead a discussion with the audience on the ideas presented by the speakers. Both the position papers and the captured discussion will be published on the workshop web site. It is the organizers’ hope that the output of this workshop, perhaps refined, can act as input to a future meeting or workshop on this topic.